Clusteval logo ClustEval clustering evaluation framework

Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:
Program Best quality Parameter set Clustering
CLARA 0.0 metric=euclidean
k=196
samples=20
Clustering
Self Organizing Maps 0.051 x=200
y=160
Clustering
Spectral Clustering 0.068 k=4 Clustering
clusterdp 0.355 k=13
dc=9.105026538673014
Clustering
HDBSCAN 0.456 minPts=19
k=162
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=195
Clustering
c-Means 0.0 k=198
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=195 Clustering
DIANA 0.0 metric=euclidean
k=200
Clustering
DBSCAN 0.503 eps=16.996049538856294
MinPts=153
Clustering
Hierarchical Clustering 0.0 method=average
k=200
Clustering
fanny 0.05 k=8
membexp=9.110000000000001
Clustering
k-Means 0.0 k=198
nstart=10
Clustering
DensityCut 0.501 alpha=0.20833333333333331
K=3
Clustering
clusterONE 0.148 s=3
d=0.5666666666666667
Clustering
Markov Clustering 0.503 I=7.460960960960961 Clustering
Transitivity Clustering 0.0 T=7.291312543481894 Clustering
MCODE 0.389 v=0.6
cutoff=4.552513269336507
haircut=F
fluff=T
Clustering